My interests within the field of architecture lie in how computational methods and data can be utilized to provide a variety of optimized results toward a specific goal. The idea of data-driven design is very interesting and works well with the current technological advances made in construction. I look forward to exploring the field of computational design and developing my skills throughout future projects.
Carbon Negative Building Framework Thesis:
As a team of four, through our in-depth research on carbon emissions, I have managed to develop a computational tool that sets out the essential steps that produce an optimal spatial design with the aim of achieving a carbon-negative building framework. The computational tool consists of a multitude of grasshopper scripts with fixed and variable parameters aimed at optimizing energy generation, energy consumption, and resource efficiency on a building scale. Additionally, the tool utilizes a stochastic aggregation engine which allows for the generation of a variety of iterations that will produce an optimal spatial design with an associated carbon rating. The proposed final model of the carbon-negative building illustrates its potential where the users (urban planners, policymakers, architects) can apply this framework within any site constraints.